v2.1

.Rbuildignore

@@ -14,4 +14,9 @@
 ^CRAN-RELEASE$
 ^customSettings$
 ^\.github$
+^app\.R$
+^rsconnect$
 ^LICENSE\.md$
+
+
+

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: safetyGraphics
 Title: Interactive Graphics for Monitoring Clinical Trial Safety
-Version: 2.0.0
+Version: 2.1.0
 Authors@R: c(
 	person("Jeremy", "Wildfire", email = "jwildfire@gmail.com", role = c("cre","aut")),
 	person("Becca", "Krouse", role="aut"),
@@ -39,11 +39,12 @@ Imports:
     rclipboard (>= 0.1.3),
     rlang (>= 0.4.11),
     safetyData (>= 1.0.0),
-    safetyCharts (>= 0.2),
+    safetyCharts (>= 0.3),
     shiny (>= 1.6.0),
     shinyjs (>= 2.0.0),
     sortable (>= 0.4.4),
     stringr (>= 1.4.0),
+    tidyr (>= 1.2.0),
     yaml (>= 2.2.1)
 VignetteBuilder: knitr
 Roxygen: list(markdown = TRUE)

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+export("%>%")
 export(app_startup)
 export(chartsNav)
 export(chartsTab)
@@ -21,6 +22,7 @@ export(makeChartExport)
 export(makeChartParams)
 export(makeChartSummary)
 export(makeMapping)
+export(makeMeta)
 export(mappingColumn)
 export(mappingColumnUI)
 export(mappingDomain)
@@ -48,10 +50,12 @@ import(datamods)
 import(dplyr)
 import(purrr)
 import(rclipboard)
+import(safetyCharts)
 import(safetyData)
 import(shiny)
 import(yaml)
 importFrom(DT,renderDT)
+importFrom(magrittr,"%>%")
 importFrom(purrr,keep)
 importFrom(purrr,map)
 importFrom(purrr,map2)
@@ -72,9 +76,12 @@ importFrom(shinyjs,useShinyjs)
 importFrom(sortable,add_rank_list)
 importFrom(sortable,bucket_list)
 importFrom(stringr,str_detect)
+importFrom(stringr,str_replace_all)
 importFrom(stringr,str_split)
 importFrom(stringr,str_to_title)
 importFrom(stringr,str_to_upper)
+importFrom(tidyr,replace_na)
+importFrom(tidyr,starts_with)
 importFrom(utils,hasName)
 importFrom(utils,zip)
 importFrom(yaml,as.yaml)

NEWS.md

@@ -1,3 +1,10 @@
+# safetyGraphics v2.1.0
+
+This release focuses on updates the safetyGraphics metadata framework:
+
+- The default metadata table has been migrated to safetyCharts and modularized. In short,`safetyGraphics::meta` is now saved as `safetyCharts::meta_aes`, `safetyCharts::meta_labs` and `safetyCharts::meta_dm`.
+- A new `makeMeta` function has been created and integrated in to the default workflow for the Shiny app. `makeMeta` provides a much more flexible framework for creating and storing metadata. See `?makeMeta` and the Cookbook and Chart Configuration vignettes for more details.
+
 # safetyGraphics v2.0.0
 
 Version 2 of {safetyGraphics} is a major update that adds the following features: 
@@ -9,7 +16,7 @@ Version 2 of {safetyGraphics} is a major update that adds the following features
 - New "Config" tab summarizing app configuration
 - Created new `safetyGraphicsInit()` app with a simple UI that can initialize the app with custom data/charts
 
-For more details, see the fully updated vingettes.
+For more details, see the fully updated vignettes.
 
 # safetyGraphics v1.1.0
 

R/_disable_autoload.R

@@ -0,0 +1,3 @@
+# Disabling shiny autoload
+
+# See ?shiny::loadSupport for more information

R/app_startup.R

@@ -3,7 +3,7 @@
 #' Prepare inputs for safetyGraphics app - run before app is initialized. 
 #' 
 #' @param domainData named list of data.frames to be loaded in to the app. Sample AdAM data from the safetyData package used by default
-#' @param meta data frame containing the metadata for use in the app. See the preloaded file (\code{?safetyGraphics::meta}) for more data specifications and details. Defaults to \code{safetyGraphics::meta}. 
+#' @param meta data frame containing the metadata for use in the app. If no metadata is provided (default value is NULL), metatdata is generated by `makeMeta()`. 
 #' @param charts list of charts in the format produced by safetyGraphics::makeChartConfig()
 #' @param mapping list specifying the initial mapping values for each data mapping for each domain (e.g. list(aes= list(id_col='USUBJID', seq_col='AESEQ')). 
 #' @param autoMapping boolean indicating whether the app should attempt to automatically detect data standards and generate mappings for the data provided. Values specified in the `mapping` parameter overwrite automatically generated mappings when both are found. Defaults to true.
@@ -22,7 +22,7 @@
 #' 
 #' @export
 app_startup<-function(domainData=NULL, meta=NULL, charts=NULL, mapping=NULL, autoMapping=NULL, filterDomain=NULL, chartSettingsPaths=NULL){
-    # Process charts metadata
+    # If charts are not provided, load them from chartSettingsPath or the safetyCharts package
     if(is.null(charts)){
         if(is.null(chartSettingsPaths)){
             charts <- makeChartConfig()
@@ -31,13 +31,8 @@ app_startup<-function(domainData=NULL, meta=NULL, charts=NULL, mapping=NULL, aut
         }
     }
 
-    # Attempt to bind chart functions if none are provided
-    charts <- charts %>% map(function(chart){
-        if(!hasName(chart,"functions")){
-            chart <- prepareChart(chart)
-        } 
-        return(chart)
-    })
+    # Prepare charts - fill in defaults, build metadata, bind functions 
+    charts <- charts %>% map(prepareChart)
 
     # Drop charts where order is negative
     orderDrops <- charts[purrr::map_lgl(charts, function(chart) chart$order < 0)]
@@ -74,6 +69,9 @@ app_startup<-function(domainData=NULL, meta=NULL, charts=NULL, mapping=NULL, aut
         }
     }
 
+    # generate a full list of metadata if none is provided
+    if(is.null(meta)) meta <- makeMeta(charts)
+
     # generate mappings and data standards
     mappingObj <- makeMapping(domainData, meta, autoMapping, mapping)
 

R/detectStandard.R

@@ -5,19 +5,19 @@
 #' This function compares the columns in the provided \code{"data"} with the required columns for a given data standard/domain combination. The function is designed to work with the SDTM and ADaM CDISC(<https://www.cdisc.org/>) standards for clinical trial data by default. Additional standards can be added by modifying the \code{"meta"} data set included as part of this package.
 #'
 #' @param data A data frame in which to detect the data standard - required.
-#' @param meta the metadata containing the data standards. - default = safetyGraphics::meta
+#' @param meta the metadata containing the data standards.
 #' @param domain the domain to evaluate - should match a value of \code{meta$domain}. Uses the first value in \code{meta$domain} if no value is provided. 
 #'
 #' @return A data frame describing the detected standard for each \code{"text_key"} in the provided metadata. Columns are \code{"domain"}, \code{"text_key"}, \code{"column"} and \code{"standard"}.
 #' @examples 
-#' detectStandard(data=safetyData::adam_adae)  #aes domain evaluated by default
-#' detectStandard(data=safetyData::adam_adlbc,domain="labs" ) 
+#' detectStandard(data=safetyData::adam_adae, meta=safetyCharts::meta_aes) 
+#' detectStandard(data=safetyData::adam_adlbc,meta=safetyCharts::meta_labs, domain="labs" ) 
 #'
 #' @importFrom stringr str_detect 
 #' 
 #' @export
 
-detectStandard <- function(data, domain=NULL, meta=safetyGraphics::meta){
+detectStandard <- function(data, domain=NULL, meta=NULL){
   if(is.null(domain)){
     domain<-unique(meta$domain)[1]
   }

R/evaluateStandard.R

@@ -13,15 +13,15 @@
 #' # Match is TRUE
 #' evaluateStandard(
 #'  data=safetyData::adam_adlbc, 
-#'  meta=meta, 
+#'  meta=safetyCharts::meta_labs, 
 #'  domain="labs", 
 #'  standard="adam"
 #' ) 
 #' 
 #' # Match is FALSE
 #' evaluateStandard(
 #'  data=safetyData::adam_adlbc, 
-#'  meta=meta, 
+#'  meta=safetyCharts::meta_labs, 
 #'  domain="labs", 
 #'  standard="sdtm"
 #' ) 
@@ -74,32 +74,43 @@ evaluateStandard <- function(data, meta, domain, standard){
     )%>%
     select(.data$text_key, .data$current, .data$valid)
 
-  stopifnot(nrow(compare_summary[["mapping"]])>0)
-
-  # count valid/invalid data elements
-  compare_summary[["total_count"]] <- compare_summary[["mapping"]] %>% nrow()
-  compare_summary[["valid_count"]] <- compare_summary[["mapping"]] %>% filter(.data$valid) %>% nrow()
-  compare_summary[["invalid_count"]] <- compare_summary[["mapping"]] %>% filter(!.data$valid) %>% nrow()
-  compare_summary[["match_percent"]] <- compare_summary[["valid_count"]] / compare_summary[["total_count"]]
-
-  standard_formatted <- standard
+    standard_formatted <- standard
   if(standard=="adam"){
     standard_formatted = "ADaM"
   }else if(standard=="sdtm"){
     standard_formatted="SDTM"
   }
 
-  if (compare_summary[["invalid_count"]]==0) {
-     compare_summary[["match"]] <- "full"
-     compare_summary[["label"]] <- standard_formatted
-  } else if(compare_summary[["valid_count"]]>0) {
-    compare_summary[["match"]] <- "partial"
-    compare_summary[["label"]] <- paste0("Partial ",standard_formatted)
-    compare_summary[["details"]]<-paste0("(", compare_summary[["valid_count"]], "/" ,compare_summary[["total_count"]], " cols/fields matched)")
-  } else {
+  if(nrow(compare_summary[["mapping"]])>0){
+    # count valid/invalid data elements
+    compare_summary[["total_count"]] <- compare_summary[["mapping"]] %>% nrow()
+    compare_summary[["valid_count"]] <- compare_summary[["mapping"]] %>% filter(.data$valid) %>% nrow()
+    compare_summary[["invalid_count"]] <- compare_summary[["mapping"]] %>% filter(!.data$valid) %>% nrow()
+    compare_summary[["match_percent"]] <- compare_summary[["valid_count"]] / compare_summary[["total_count"]]
+
+    if (compare_summary[["invalid_count"]]==0) {
+      compare_summary[["match"]] <- "full"
+      compare_summary[["label"]] <- standard_formatted
+    } else if(compare_summary[["valid_count"]]>0) {
+      compare_summary[["match"]] <- "partial"
+      compare_summary[["label"]] <- paste0("Partial ",standard_formatted)
+      compare_summary[["details"]]<-paste0("(", compare_summary[["valid_count"]], "/" ,compare_summary[["total_count"]], " cols/fields matched)")
+    } else {
+      compare_summary[["match"]] <- "none"
+      compare_summary[["label"]] <- "No Match"
+    }
+  }else{
+    # No values provided for standard in this domain
+    compare_summary[["total_count"]] <- 0
+    compare_summary[["valid_count"]] <- NA
+    compare_summary[["invalid_count"]] <- NA
+    compare_summary[["match_percent"]] <- 0
     compare_summary[["match"]] <- "none"
     compare_summary[["label"]] <- "No Match"
   }
+
+
+
 
   return(compare_summary)
 }

R/makeChartConfig.R

@@ -27,24 +27,21 @@
 #' }
 #' @export
 
-makeChartConfig <- function(dirs, packages="safetyCharts", packageLocation="config", sourceFiles=TRUE){
+makeChartConfig <- function(dirs, packages="safetyCharts", packageLocation="config", sourceFiles=FALSE){
     if(missing(dirs)) dirs<-NULL
 
     # add local package installation to dirs if specified in packages
     if(!is.null(packages)){
         for(package in packages){
             packageFound<-FALSE
-            for(lib in .libPaths()){
-
-                packageDir<-paste(lib,package,packageLocation, sep="/")               
-                if(file.exists(packageDir)) {
-                    loaded <- do.call(require,list(package))
-                    if(!loaded) do.call(library,list(package)) #Attach the library to the search list if it is installed
-                    message("- Found the {",package,"} package and added ", packageDir," to list of chart locations.")
-                    packageFound<-TRUE   
-                    dirs<-c(dirs, packageDir)
-                    break               
-                }
+            packageDir <- system.file(packageLocation, package = package)
+            if(file.exists(packageDir)) {
+                loaded <- do.call(require,list(package))
+                if(!loaded) do.call(library,list(package)) #Attach the library to the search list if it is installed
+                message("- Found the {",package,"} package and added ", packageDir," to list of chart locations.")
+                packageFound<-TRUE   
+                dirs<-c(dirs, packageDir)
+                break               
             }
             if(!packageFound){
                 message("{",package, "} package not found or '",packageLocation,"' folder does not exist, please install package and confirm that specified folder is found.")

R/makeMapping.R

@@ -1,7 +1,7 @@
 #' Create data mapping based on data standards and user input
 #' 
 #' @param domainData named list of data.frames to be loaded in to the app. Sample AdAM data from the safetyData package used by default
-#' @param meta data frame containing the metadata for use in the app. See the preloaded file (\code{?safetyGraphics::meta}) for more data specifications and details. Defaults to \code{safetyGraphics::meta}. 
+#' @param meta data frame containing the metadata for use in the app. 
 #' @param customMapping optional list specifying initial mapping values within each data mapping (e.g. list(aes= list(id_col='USUBJID', seq_col='AESEQ')). 
 #' @param autoMapping boolean indicating whether the app should use `safetyGraphics::detectStandard()` to detect data standards and automatically generate mappings for the data provided. Values specified in the `customMapping` parameter overwrite auto-generated mappings when both are found. Defaults to true.
 #' 
@@ -21,7 +21,13 @@ makeMapping <- function(domainData, meta, autoMapping, customMapping ){
         })
         names(standards)<-names(domainData)
 
-        auto_mapping_list <- standards %>% map(~.x$mapping)
+        auto_mapping_list <- standards %>% map(function(standard){
+            if(standard$standard=="none"){
+                return(data.frame(domain=character(), text_key=character(), current=character(), valid=logical()))
+            }else{
+                return(standard$mapping)
+            }
+        })        
         auto_mapping_df<-bind_rows(auto_mapping_list, .id = "domain") %>% select(-.data$valid)
     }else{
         # otherwise initialize NULL standards/mapping